Senior Data Scientist - Fraud Data Infrastructure & Automation
Tasks
- Automate data exploration and anomaly detection
- Build and evaluate fraud and identity models
- Conduct end to end machine learning and analytics lifecycle
- Design scalable data pipelines and workflows
- Integrate third party data vendors and external datasets
- Lead research for new data sources and algorithms
- Maintain data quality and integrity
- Mentor peers and junior data scientists
- Perform post deployment monitoring
- Present findings and recommendations to stakeholders
Perks/Benefits
- N/A
Skills/Tech-stack
AUC | Agentic AI | Airflow | Calibration | Data Pipelines | Data Quality | Data quality monitoring | Databricks | Feature Engineering | Fraud Detection | Identity verification | LLMs | Langchain | Langgraph | Language Processing | Lift | Machine Learning | Model Evaluation | Natural Language | Natural Language Processing | Near Real Time Data Pipelines | Near-Real-Time data | Near-real-time | PyTorch | Python | Quality monitoring | Ray | Real-time data pipelines | Risk Modeling | SQL | Scikit-learn | Spark | Stability | TensorFlow
Education
Roles
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